3 papers
cs.LG2020
A New Modal Autoencoder for Functionally Independent Feature Extraction
Yuzhu Guo, Kang Pan, Simeng Li +3
Autoencoders have been widely used for dimensional reduction and feature extraction. Various types of autoencoders have been proposed by introducing regularization terms. Most of t…
cs.CV2018
Boosted Convolutional Neural Networks for Motor Imagery EEG Decoding with Multiwavelet-based Time-Frequency Conditional Granger Causality Analysis
Yang Li, Mengying Lei, Xianrui Zhang +4
Decoding EEG signals of different mental states is a challenging task for brain-computer interfaces (BCIs) due to nonstationarity of perceptual decision processes. This paper prese…
eess.SP2018
A Parametric Time Frequency-Conditional Granger Causality Method Using Ultra-regularized Orthogonal Least Squares and Multiwavelets for Dynamic Connectivity Analysis in EEGs
Yang Li, Mengying Lei, Weigang Cui +2
Objective: This study proposes a new parametric TF (time frequency) CGC (conditional Granger causality) method for high precision connectivity analysis over time and frequency in m…